CN114500549A

CN114500549A - Method, apparatus, and medium to deploy k8s hosting cluster for users in public cloud

Info

Publication number: CN114500549A
Application number: CN202011268416.3A
Authority: CN
Inventors: 彭世柱
Original assignee: Tianyi Cloud Technology Co Ltd
Current assignee: Tianyi Cloud Technology Co Ltd
Priority date: 2020-11-13
Filing date: 2020-11-13
Publication date: 2022-05-13
Anticipated expiration: 2040-11-13
Also published as: CN114500549B

Abstract

The present disclosure relates to methods, apparatus, and media for deploying k8s hosted clusters for users in a public cloud. The present disclosure provides a method of deploying k8s hosting clusters in a public cloud for users, wherein the users have at least one host and the at least one host constitutes the k8s hosting cluster, the method comprising: creating a k8s management cluster in the public cloud; and containerizing Master components of the k8s hosting cluster to form a Master container; deploying the Master container in the k8s management cluster, wherein the deploying comprises: creating an orchestration file for the k8s hosting cluster in the k8s managing cluster; and creating, by a controller in the k8s management cluster, a corresponding number of containers in the k8s management cluster for each subcomponent of the Master container using the orchestration file to form a highly available k8s hosted cluster.

Description

Method, apparatus, and medium to deploy k8s hosted clusters for users in a public cloud

Technical Field

The present disclosure relates generally to the field of container orchestration tool k8s technology, and more particularly to methods, apparatus, and media for deploying k8s hosted clusters for users in a public cloud.

Background

K8s is an abbreviation for Kubernetes. Kubernetes is a container arrangement engine of Google open source, is the most widely used container arrangement tool at present, and solves the problem of large-scale deployment after containerization is applied. In kubernets, multiple containers can be created, each container runs an application instance, and then management, discovery and access of the group of application instances are realized through a built-in load balancing strategy, and no operation and maintenance personnel are required to perform complicated manual configuration and processing.

The components of Kubernetes fall into two categories: master component and Node component. The Master component comprises Etcd, Kube-apiserver, Kube-scheduler and Kube-controller-manager. The Node components include Kubelet and Kube-proxy. In the Master component, Etcd is a key-value database, and the data of k8s are stored in Etcd; the Kube-apiserver is an HTTP server and exposes RESTAPI to external users and Node nodes; the Kube-scheduler is a scheduler, which always listens to Pod (Pod) in the cluster through the API of Kube-apiserver, and then schedules it to a Node. The Kube-controller-manager will also always listen to the Kube-API's API, performing some looping tasks.

In a conventional k8s cluster deployment architecture, a highly available k8s cluster is deployed, at least three nodes are required, and a Master component is deployed on each Node and shares a host with the Node components.

In the public cloud mode, such a scenario is usually encountered: the application scale of the user is small, and one or two hosts can meet the requirement generally. At this time, if a conventional k8s cluster is to be built, the user needs to purchase at least three hosts, which is costly. Therefore, the mode of hosted clusters is very suitable for small users.

There are many implementations of hosting clusters: the simplest method is to select three hosts, and when one user opens one hosting cluster, the configuration and the number of the working nodes are selected. For the present example, a set of high available masters components of k8s are deployed on the three hosts (multiple masters can be deployed on one host). However, this approach lacks the ability to scale out, and they may only deploy masters of N clusters at best. Therefore, it is not feasible to run the Master hosting the cluster directly on the host in a physical way.

Therefore, there is a need in the art for techniques to be able to deploy scalable k8s hosting clusters in a public cloud for users with any number of hosts.

Disclosure of Invention

The following presents a simplified summary of the disclosure in order to provide a basic understanding of some aspects of the disclosure. However, it should be understood that this summary is not an exhaustive overview of the disclosure. It is not intended to identify key or critical elements of the disclosure or to delineate the scope of the disclosure. Its sole purpose is to present some concepts of the disclosure in a simplified form as a prelude to the more detailed description that is presented later.

According to one aspect of the present disclosure, there is provided a method of deploying a k8s hosted cluster for users in a public cloud, wherein the users have at least one host and the at least one master hosts the k8s hosted cluster, the method comprising: creating a k8s management cluster in the public cloud; and containerizing Master components of the k8s hosting cluster to form a Master container; deploying the Master container in the k8s management cluster, wherein the deploying comprises: creating an orchestration file for the k8s hosting cluster in the k8s managing cluster; and creating, by a controller in the k8s management cluster, a corresponding number of containers in the k8s management cluster for each subcomponent of the Master container using the orchestration file to form a highly available k8s hosted cluster.

According to another aspect of the present disclosure, there is provided a server in a public cloud, including: a memory having instructions stored thereon; and a processor configured to execute instructions stored on the memory to perform a method according to the above aspects of the disclosure.

According to yet another aspect of the present disclosure, there is provided a computer-readable storage medium comprising computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform a method according to the above-mentioned aspect of the present disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the disclosure.

The present disclosure may be more clearly understood from the following detailed description with reference to the accompanying drawings, in which:

FIG. 1 illustrates a flow diagram of a process to deploy a k8s hosting cluster for users in a public cloud according to one embodiment of the present disclosure;

FIG. 2 shows a schematic diagram of a deployment architecture of a hosting cluster according to one embodiment of the present disclosure;

FIG. 3 illustrates a schematic diagram of an orchestration documentation and deployment tool hosting a cluster Master according to one embodiment of the present disclosure;

fig. 4 illustrates an exemplary configuration in which network-side servers hosting clusters for deployment k8s for users in a public cloud may be implemented according to one embodiment of the present disclosure.

Detailed Description

The following detailed description is made with reference to the accompanying drawings and is provided to assist in a comprehensive understanding of various exemplary embodiments of the disclosure. The following description includes various details to aid understanding, but these details are to be regarded as examples only and are not intended to limit the disclosure, which is defined by the appended claims and their equivalents. The words and phrases used in the following description are used only to provide a clear and consistent understanding of the disclosure. In addition, descriptions of well-known structures, functions, and configurations may be omitted for clarity and conciseness. Those of ordinary skill in the art will recognize that various changes and modifications of the examples described herein can be made without departing from the spirit and scope of the disclosure.

The present inventors have recognized that it is not feasible in the prior art to run a Master hosting a cluster directly on a host. Therefore, the inventor proposes to operate the Master of the hosted cluster in a k8s management cluster, so that the Master container of the hosted cluster is equivalent to an ordinary container in the management cluster.

Fig. 1 illustrates a flow diagram of a process 100 to deploy a k8s hosting cluster for users in a public cloud according to one embodiment of the disclosure. A user may have at least one host and request to open a k8s hosting cluster. The user may select the configuration and number of hosts at boot-up. At least one host of a user constitutes the k8s hosting cluster.

At step 101, the process starts. At this step, a k8s management cluster is created in the public cloud.

At step 102, the Master components of the k8s hosting cluster are containerized to form a Master container.

At step 103, the Master container is deployed in the k8s management cluster. This deployment may be achieved by: creating a choreography file in the k8s management cluster for the k8s hosted cluster; and creating, by a controller in the k8s management cluster, a corresponding number of containers for each subcomponent of the Master container in the k8s management cluster using the orchestration file to form a highly available k8s hosted cluster.

Notably, this layout file is parsable by native k8 s. When the user has one or 2 hosts, the orchestration file specifies the etcd, kube-apiserver, kube-controller-manager, kube-scheduler sub-components of the Master container to create 3 containers, 2 containers, respectively.

The process 100 may further include: the k8s manages the controller in the cluster to sequentially launch each of the 3 containers of the etcd subcomponent according to the orchestration file.

The process 100 may further include: the controller monitors a layout file; and responding to the monitoring of the layout file, the controller deploys the Master container in the k8s management cluster.

The process 100 may further include: modifying the orchestration file to adapt to changes in the number of hosts of the user.

As described above, a user in a public cloud may have only one or two hosts. In this case, the user cannot be provided with a highly available k8s hosting cluster using existing techniques. The present process solves this problem. When a user has only one or two hosts, 3 containers are created in the k8s management cluster for the etcd subcomponent of the Master component of the user-created k8s hosting cluster to meet the requirements of a highly available cluster.

Fig. 2 shows a schematic diagram of a deployment architecture of a hosting cluster according to one embodiment of the present disclosure.

As shown in fig. 2, k8s administrative clusters are created in the public cloud to run Master component containers for the various hosted clusters. For example, two hosted

clusters

6443 and 6444 are shown in fig. 2, belonging to two users, respectively. The Master components of the two hosted clusters are containerized as Master containers running in the k8s managed cluster. Although there are only two nodes per user, 3 containers are created in the Master container for the etcd subcomponent to meet the requirements of the highly available hosted cluster. It is noted that the other sub-components of the Master component, kube-api, kube-controller-manager, kube-scheduler, may create only 2 containers for it. These are implemented by programming files and using a controller to listen to the programming files. This is described further below.

Fig. 2 illustrates a deployment architecture of a hosting cluster. Except for the Etcd, all the services in FIG. 2 are stateless services, and they can be deployed by a common Deployment workload. Etcd is a stateful service, where an open-source Etcd-operator containerization scheme may be used. And the data of the Etcd can use distributed storage or local storage. Under the deployment architecture, any container instance of the Master is hung up and can be recovered within the second level. In addition, when the scale of the hosting cluster becomes large, namely the number of Master containers becomes large, the problem can be perfectly solved only by performing transverse expansion on the nodes of the management cluster.

The Kubeadm tool is only suitable for deploying masters of the clusters to the hosts, and when the masters need to be containerized and run in a k8s cluster according to the invention, another method is found for the deployment of the masters. Therefore, the invention designs an arrangement file for representing the hosted cluster Master based on a CRD (Custom Resource Definition) mechanism of k8s, then develops a corresponding controller, monitors the arrangement file, and then deploys the hosted cluster Master in the management cluster by the controller.

Fig. 3 shows a schematic diagram of an orchestration documentation and deployment tool of a hosted cluster Master according to one embodiment of the present disclosure. As shown in fig. 3, k8s manages two files CR already formed in the cluster. The controller Operator continuously listens for the presence or change of a CR (Custom Resource). In response to snooping the presence or change of the CR, the Operator creates individual containers for the Master component.

The working mechanism of the orchestration file and the Operator is described in detail below. The master component of K8s includes etcd, kube-apiserver, kube-controller-manager and kube-scheduler; at least three containers of the etcd form an etcd cluster to ensure high availability, and the other containers of the etcd cluster need two containers to ensure high availability. This orchestration file, native k8s, is not parsable, but the Operator can identify this orchestration file and from it, create a corresponding number of containers for each component in the cluster. Where the three containers of the etcd assembly, rather than operating independently, need to be grouped into an etcd cluster. The operator controls the starting sequence of each etcd container, and when the first container is up, the etcd cluster has only one instance; the operator continues to start the second and adds the second container to the first cluster of etcd containers, thus forming a two-instance etcd cluster; this is repeated until all etcd containers are added to form a three-container etcd cluster.

If the user increases or decreases the host usage due to his own needs, adjustments can be made by modifying the orchestration file. The controller Operator listens for changes to the orchestration file and may create or delete the corresponding sub-component container. Thus, the present invention enables a highly available scalable k8s hosting cluster for users.

For example, one exemplary embodiment of the present invention may be implemented by: (some more detailed description is best given of the following operations)

1. The hosting cluster is suitable for public cloud scenarios. The user selects to open a k8s hosting cluster on the public cloud, and selects the configuration and number of the working nodes.

2. After receiving the request, the public cloud front end sends a request to the k8s management cluster, and creates a cr (custom resource) object in the k8s management cluster.

3. After the Operator in the management cluster monitors that a CR object is generated, an orchestration file that can be understood by the native k8s is created. From these orchestration files, the kube-controller-manager component in the management cluster creates Master containers such as kube-api over, kube-controller-manager, kube-scheduler, etc. hosting the cluster. The Operator also needs to create a specified number of etcd containers in order until they make up an etcd cluster.

4. When the Master containers of the hosting cluster are all operated, the front end of the public cloud continues to send a request IaaS layer to request to obtain working node hosts, then the Worker components of k8s are installed on the hosts, and the addresses of the masters configured for the Worker are the addresses of the containers just created in the management cluster. Thus, a Master container and a Worker node host which run in the management cluster form a complete hosting cluster and are delivered to the user. Additionally, the Master modules running on top are all container mirrors using an open source. Except that the Operator, this container, needs to be developed autonomously in accordance with the logic described above.

The present invention has at least one of the following advantages and effects, compared to the prior art. First, compared with the traditional k8s cluster deployment mode, the method can reduce the resource cost of small users, and simultaneously can ensure the high availability of the hosted cluster. Secondly, compared with a mode that a Master is intensively deployed in three hosts, the system has better horizontal expansibility and high availability.

Fig. 4 illustrates an exemplary configuration in which a network-side server 1200 hosting a cluster for deployment of k8s to users in a public cloud according to one embodiment of the present disclosure may be implemented.

Computing device 1200 is an example of a hardware device to which the above-described aspects of the disclosure can be applied. Computing device 1200 may be any machine configured to perform processing and/or computing. Computing device 1200 may be, but is not limited to, a workstation, a server, a desktop computer, a laptop computer, a tablet computer, a Personal Data Assistant (PDA), a smart phone, an in-vehicle computer, or a combination thereof.

As shown in fig. 4, computing device 1200 may include one or more elements that may be connected to or communicate with bus 1202 via one or more interfaces. The bus 2102 may include, but is not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an enhanced ISA (eisa) bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus, among others. Computing device 1200 may include, for example, one or more processors 1204, one or more input devices 1206, and one or more output devices 1208. The one or more processors 1204 may be any kind of processor and may include, but are not limited to, one or more general-purpose processors or special-purpose processors (such as special-purpose processing chips). The processor 1202 may be configured to implement, for example, a process of deploying the k8s hosting cluster for users in a public cloud. Input device 1206 may be any type of input device capable of inputting information to a computing device and may include, but is not limited to, a mouse, a keyboard, a touch screen, a microphone, and/or a remote controller. Output device 1208 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, a video/audio output terminal, a vibrator, and/or a printer.

Computing device 1200 may also include or be connected to a non-transitory storage device 1214, which non-transitory storage device 1214 may be any non-transitory and may implement a storage of data, and may include, but is not limited to, disk drives, optical storage devices, solid state memory, floppy disks, flexible disks, hard disks, magnetic tape, or any other magnetic medium, compact disks or any other optical medium, cache memory, and/or any other memory chip or module, and/or any other medium from which a computer may read data, instructions, and/or code. Computing device 1200 may also include Random Access Memory (RAM)1210 and Read Only Memory (ROM) 1212. The ROM 1212 may store programs, utilities or processes to be executed in a non-volatile manner. The RAM 1210 may provide volatile data storage, and store instructions related to the operation of the computing device 1200. Computing device 1200 may also include a network/bus interface 1216 coupled to a data link 1218. The network/bus interface 1216 may be capable of enabling communication with external devices andand/or any kind of device or system for network communication, and may include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication device, and/or a chipset (such as bluetooth)^TMDevices, 802.11 devices, WiFi devices, WiMax devices, cellular communications facilities, etc.).

The present disclosure may be implemented as any combination of apparatus, systems, integrated circuits, and computer programs on non-transitory computer readable media. One or more processors may be implemented as an Integrated Circuit (IC), an Application Specific Integrated Circuit (ASIC), or a large scale integrated circuit (LSI), a system LSI, or a super LSI component that performs some or all of the functions described in this disclosure.

The present disclosure includes the use of software, applications, computer programs or algorithms. Software, applications, computer programs, or algorithms may be stored on a non-transitory computer readable medium to cause a computer, such as one or more processors, to perform the steps described above and depicted in the figures. For example, one or more memories store software or algorithms in executable instructions and one or more processors may associate a set of instructions to execute the software or algorithms to provide various functionality in accordance with embodiments described in this disclosure.

Software and computer programs (which can also be referred to as programs, software applications, components, or code) include machine instructions for a programmable processor, and can be implemented in a high-level procedural, object-oriented, functional, logical, or assembly language, or machine language. The term "computer-readable medium" refers to any computer program product, apparatus or device, such as magnetic disks, optical disks, solid state storage devices, memory, and Programmable Logic Devices (PLDs), used to provide machine instructions or data to a programmable data processor, including a computer-readable medium that receives machine instructions as a computer-readable signal.

By way of example, computer-readable media may comprise Dynamic Random Access Memory (DRAM), Random Access Memory (RAM), Read Only Memory (ROM), electrically erasable read only memory (EEPROM), compact disk read only memory (CD-ROM) or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which may be used to carry or store desired computer-readable program code in the form of instructions or data structures and which may be accessed by a general-purpose or special-purpose computer or a general-purpose or special-purpose processor. Disk or disc, as used herein, includes Compact Disc (CD), laser disc, optical disc, Digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above are also included within the scope of computer-readable media.

Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In some cases, multi-task processing and parallel processing may be advantageous.

Claims

1. A method of deploying a k8s hosting cluster for users in a public cloud, wherein the users have at least one host and the at least one host constitutes the k8s hosting cluster, the method comprising:

creating a k8s management cluster in the public cloud; and

containerizing Master components of the k8s hosting cluster to form a Master container;

deploying the Master container in the k8s management cluster, wherein the deploying comprises:

creating an orchestration file for the k8s hosting cluster in the k8s managing cluster; and

creating, by a controller in the k8s management cluster, a corresponding number of containers in the k8s management cluster for each subcomponent of the Master container using the orchestration file to form a highly available k8s hosted cluster.

2. The method of claim 1, wherein when the user has one or 2 hosts, the orchestration file specifies that the Master container's etcd, kube-api, kube-controller-manager, kube-scheduler subcomponents create 3 containers, 2 containers, respectively.

3. The method of claim 2, wherein the k8s manages each of the 3 containers of the etcd subcomponent sequentially by the controller in the cluster according to the orchestration file.

4. The method of claim 1, further comprising:

the controller monitors a layout file; and

in response to monitoring the layout file, the controller deploys the Master container in the k8s management cluster.

5. The method of claim 1, further comprising:

modifying the orchestration file to adapt to changes in the number of hosts of the user.

6. A server in a public cloud, comprising:

a memory having instructions stored thereon; and

a processor configured to execute instructions stored on the memory to perform the method of any of claims 1 to 5.

7. A computer-readable storage medium comprising computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform the method of any one of claims 1-7.